What is Synthetic Data

Synthetic data is fake data (not exactly fake), also called artificial data. It is a type of data that is generated using algorithms. These algorithms are trained on real-world data samples to learn the correlations, statistical properties, and data structures. Once trained, these models can generate synthetic data that is identical to the real-world training data.

Synthetic data is widely used for training machine learning models in various industries like car manufacturing, banks, drones, factories, hospitals, retailers, robotics, and science.

Now that we know what synthetic data is and where it is used, let’s cover the need for synthetic data.

The need for Synthetic data

We live in a world where data is everything, and this is one of the reasons why we need synthetic data. Real-world data is difficult, expensive, and time-consuming to obtain, while Synthetic data is cost-effective, programmable, and scalable, making it an inexpensive alternative to real-world data.

Synthetic data is widely used for training machine-learning and deep-learning models. These models require large, well-labeled datasets, but it can be difficult and time-consuming to collect such data at scale, and here synthetic data comes to the rescue.

Though synthetic data is identical to real-world data, it’s still not real data, but it can address privacy issues and reduce bias by ensuring users have the data diversity to represent the real world.

In a report on synthetic data, Gartner predicted that by 2030, most of the data used in AI will be artificially generated by rules, statistical models, simulations, or other techniques.

The report said, “The fact is, you won’t be able to build high-quality, high-value AI models without synthetic data.”

Following are the companies leveraging synthetic data:

• Amazon is using synthetic data to train Alexa's language system.
• Google's Waymo uses synthetic data to train its self-driving cars.
• Health insurance company Anthem works with Google Cloud to generate synthetic data.
• American Express and J.P. Morgan are using synthetic financial data to improve fraud detection.
• Roche is using synthetic medical data for clinical research.
• German insurance company Provinzial tests synthetic data for predictive analytics.